---
title: 'LLM App Architectures'
description: 'The different types of LLM applications (that can be used in agenta).'
---


There are multitude of architectures or pipelines for LLM applications. We discuss here the main ones. 

## The Single Prompt Architecture

This architecture is the simplest. The LLM application is a simple wrapper around one prompt / LLM call. 

In agenta you can [create such LLM apps from the UI](/getting_started/getting-started-ui). Or you can [use your own code](quickstart/getting-started-code) in case that your [model is not supported](tutorials/deploy-mistral-model) (or you would like to add some custom logic for pre-processing or post-processing the inputs).

<img className="dark:hidden" height="600" src="/images/learning/single_prompt_light.png" />
<img className="hidden dark:block" height="600" src="/images/learning/single_prompt_dark.png" />


## The Chain-of-prompt Architecture

The chain of prompt architecture as its name suggest is based on calling an LLM and then injecting the output into a second call as shown in the figure. 

<img className="dark:hidden" width="300" src="/images/learning/chain-of-prompts_light.png"/>
<img className="hidden dark:block" width="300" src="/images/learning/chain-of-prompts_dark.png" />

## The Retrieval Augment Generation Architecture

## The Agent architecture

## Chat vs. Flow